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investigation and characteristics approaches for nanoscience materials using networking

Dr.S.Tamil,

Published in International Journal of Advanced Research in Electronics, Communication & Instrumentation Engineering and Development

ISSN: 2347 -7210          Impact Factor:1.9         Volume:1         Issue:2         Year: 08 February,2014         Pages:53-60

International Journal of Advanced Research in Electronics, Communication & Instrumentation Engineering and Development

Abstract

The grid computing is a key to concern when developing parallel operation and distributed computing applications. In this paper the grid management infrastructure is coupled with a performance for local grid load balancing. Each grid scheduler utilises predictive application performance data and an iterative heuristic algorithm to operator. On-demand data streaming is introduced to avoid data overflow using repertory strategies. Experimental results show that balance among task executions with on-demand data streaming is required to improve overall performance Agents cooperate with each other to balance workload in the global grid environment using service advertisement and discovery mechanisms.

Kewords

Grid computing, agents, network modeling, Genetic algorithm, Task schedule.

Reference

[1]. J. H. Holland, Adaptation in Natural and Artificial Systems, University of Michigan Press, 2012. [2]. B. Allcock, J. Bester, J. Bresnahan, A. L. Chervenak, I. Foster, C. Kesselman, S. Meder, V. Nefedova, D. Quesnal, and S. Tuecke, “Data Management and Transfer in High Performance Computational Grid Environments”, Parallel Computing, Vol. 28, No. 5, pp. 749-771, 2010. [3]. I. Foster and C. Kesselman, “Globus: A Metacomputing Infrastructure Toolkit”, Int. J. Supercomputer Applications, vol. 11, No. 2, 2010, pp.115-128. [4] F. Berman, R. Wolski, S. Figueira, J. Schopf, and G. Shao, Application-level scheduling on distributed heterogeneous networks, in “Proc. 2006 Supercomputing”, Pittsburgh, PA, USA, 2006. [5] J. Cao, D. J. Kerbyson, E. Papaefstathiou, and G. R. Nudd, Performance modelling of parallel and distributed computing using PACE, in “Proc. 19th IEEE International Performance, Computing and Communication Conference”, pp. 485-492, Phoenix, AZ, USA, 2011. [6] J. Cao, D. J. Kerbyson, and G. R. Nudd, Dynamic application integration using agent-based operational administration, in “Proc. 5th International Conference on the Practical Application of Intelligent Agents and Multi-Agent Technology”, pp. 393-396, Manchester, UK, 2010. [7] J. Cao, D. J. Kerbyson, and G. R. Nudd, High performance service discovery in large-scale multi-agent and mobile-agent systems, Int. J. Software Engineering and Knowledge Engineering Special Issue on Multi-Agent Systems and Mobile Agents 5 (October 2009), 621-641. BIOGRAPHY